Geospatial Data Science in Python
Syllabus
Schedule
Section 401
Section 402
Content
Assignments
Overview
Section 401
Section 402
Resources
GitHub
Canvas
Ed Discussion
7. Working with APIs
Weekly Course Content
1. Exploratory Data Science in Python
2. Data Visualization Fundamentals
3. More Interactive Data Viz, Intro to Vector Data & GeoPandas
4. Geospatial Analysis & Mapping
5. More Geospatial Analysis: Street Networks and Raster Data
6. Web Scraping
7. Working with APIs
8. Analyzing and Visualizing Large Datasets
9. From Notebooks to the Web: Part 1
10. From Notebooks to the Web: Part 2
11. Clustering Analysis in Python
12. Predictive Modeling with Scikit-Learn, Part 1
13. Predictive Modeling with Scikit-Learn, Part 2
14. Advanced Raster Analysis
On this page
New Packages
Reference Materials
Week 7: Getting Data, Part 2: Working with APIs
Content for lectures 7A and 7B
View materials:
MUSA-550-Fall-2023/week-7
HTML slides:
Lecture 7A
Lecture 7B
Executable slides:
Lecture 7A
Lecture 7B
New Packages
cenpy
pygris
textblob
transformers
wordcloud
Reference Materials
Census API User Guide
Census API Tutorial
Variable Names for Census Fields
cenpy
Documentation
Introductory guide
Census Geographic Identifiers (GEOIDs)
pygris
Documentation
textblob
Documentation
transformers
Documentation
wordcloud
Documentation
6. Web Scraping
8. Analyzing and Visualizing Large Datasets